In an application of background speech recognition to medical transcription, the automatic speech recognition (“ASR”) process is run “off line”, without real-time clinician interaction. The speaker dictates a report normally, the audio is stored on a fileserver and the speech recognition process is run on the audio file in batch mode at a later time. Draft transcriptions produced by the ASR process may then be edited by the clinician or by a Medical Transcriptionist (“MT”) before being added to the medical record. An example of this type of ASR application is the EditScript product from eScription.
In healthcare applications, background speech recognition has particular advantages. For example, the clinician need not significantly change their workflow relative to how they normally dictate. Medical transcriptionists can edit the draft documents much faster than they can type them, and with greater facility than a clinician can edit. Further, since ASR computation is not restricted to the environment of the healthcare facility, extensive computational resources may be brought to bear on the difficult problem of speech recognition. Also because the ASR resources are off-site, clinicians can dictate at any time or place, unrestricted by the availability of a particular workstation.
Although background speech recognition has many benefits, in some health care applications, other considerations can become significant that make background speech recognition less beneficial. For example, an Emergency Department may require rapid turnaround time for dictated Radiology reports. In some circumstances, it may be a requirement that documents are signed immediately after dictation. Thus, many healthcare organizations opt for deployment of real-time ASR systems, which negates some of the aforementioned advantages of background ASR.